A5084336126- Ethics and Social Impacts of AI
- Mobile Crowdsensing and Crowdsourcing
- Explainable Artificial Intelligence (XAI)
- Psychology of Moral and Emotional Judgment
- Innovative Human-Technology Interaction
University of California, Berkeley
2023-2024
Emerging methods for participatory algorithm design have proposed collecting and aggregating individual stakeholders' preferences to create algorithmic systems that account those values. Drawing on two years of research across public school districts in the United States, we study how families use students' schools meet their goals context student assignment systems. We find preference language, i.e. structure which participants must express needs decision-maker, shapes opportunities...
Understanding how people perceive algorithmic decision-making is remains critical, as these systems are increasingly integrated into areas such education, healthcare, and criminal justice. These perceptions can shape trust in, compliance with, the perceived legitimacy of automated systems. Focusing on San Francisco's decade-long policy school assignments, we draw procedural distributive justice theory to investigate parents' fairness assignment system. We find that key differences in...